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As a part of the transition in higher-level energy systems, distributed cross-sectoral energy systems (DCESs) play a crucial role in providing flexibility in covering residual load (RL). However, there is currently no method available to quantify the potential flexibility of DCESs in covering RL. This study aimed to address this gap by comparing the RL demand of a higher-level energy system with the electricity flow between a DCES and the electricity grid. This can allow for the quantification of the flexibility of DCES operation. Our approach was to categorize existing methods for flexibility quantification and then propose a new method to assess the flexibility of DCESs in covering RL. For this, we introduced a new quantification indicator called the Flexibility Deployment Index (FDI), which integrates two factors: the RL of the higher-level energy system and the electricity purchase and feed-in of a DCES. By normalizing both factors, we could compare the flexibility to cover RL with respect to different DCES concepts and scenarios. To validate the developed quantification method, we applied it to a case study of a hospital's DCES in Germany. Using an MILP optimization model, we analyzed the variation in FDI for different technology concepts and scenarios, including fixed electricity tariffs, dynamic electricity tariffs, and CO2-emission-optimized operation. The results of our calculations and the application of the FDI indicate that high-capacity combined heat and power units combined with thermal storage units provide higher flexibility. Additionally, the results highlight higher flexibility provision during the winter period compared to the summer period. However, further application and research are needed to confirm the robustness and validity of the FDI assessment. Nonetheless, the case study demonstrates the potential of the new quantification method. [ABSTRACT FROM AUTHOR]

By immediately responding to achievement progress data, teachers can improve students' performance by using curriculum-based measurement. However, there are studies showing that teachers are prone to make biased judgments about the students providing the data. The present investigation experimentally examined whether pre-service teachers in Germany were biased by the use of gender stereotypes when judging students' achievement derived from progress data. N = 100 pre-service teachers received graphs that depicted the development of either oral reading fluency or math achievement of girls and boys over a time interval of 11 weeks. The results obtained confirmed the hypotheses partially. The participants did not favor girls over boys on average. However, they judged achievement in reading to be higher for girls than for boys, and math achievement to be higher for boys than for girls. The results suggest that gender stereotypes (boys are good at math, girls are good at reading) are still prevalent in pre-service teachers. [ABSTRACT FROM AUTHOR]

Many pests damage pea crops, which potentially leads to reduced quality and yield losses. Since pests occur at different phenological growth stages of pea crops, the prediction of growth stages, for example as BBCH stages, is beneficial. In this study, three models have been developed to simulate growth stages of grain and green pea crops, for the latter with early and late sowing dates. All data, such as BBCH stages and air temperature, were collected in Germany in a three-year study under practical farming conditions at 415 sample sites. For the development of each model, a Gompertz regression model based on the observed data was performed. The model validation suggests that each model precisely and reliably predicts pea crop growth stages for spring-sown peas. Amongst others, the RMSEIndex for grain peas was 3.4; for green peas, early and late sowing dates, respectively, they were 3.4 and 4.5. SIMONTO-Pea (SIMulation of ONTOgenesis) is the first model that predicts detailed pea crop growth stages based on the BBCH scale. This innovation is especially beneficial for users such as advisors and farmers dealing with spring-sown pea crops as a decision support system in monitoring and pest management according to pea crop growth stages. [ABSTRACT FROM AUTHOR]

Rising global temperatures have increased the need for research into human adaptability and comfort in buildings. To reduce comfort-related energy demands, low-energy-consumption alternatives for space cooling, such as personal environmental control systems (PECS), are being investigated. The implementation of PECS in office buildings is still underway, and little is known about how occupants' expectations can influence their satisfaction with PECS and indoor environmental quality. This study examines the influence of tailored information and occupants' comfort expectations on their thermal perceptions and satisfaction with a personal ceiling fan. Seventy-six participants completed an online questionnaire and attended a half-day session at 30 °C in a climate chamber in Germany. A manipulation technique to activate personal norms was used to test the influence of information on expectations. Results indicated higher reported thermal comfort in participants with more positive thermal expectations, regardless of their expectations of the building systems. These effects were largely moderated by personal norms, indicating the importance of activating normative motivations to increase thermal comfort. Occupants with negative expectations improved their perceptions of the fan when making personal adjustments to stay comfortable. However, this effect was not moderated by personal norms. Practical implications focus on manipulating occupants' comfort expectations, e.g., by providing occupants with normative messages and individual control, to achieve greater comfort and acceptance of personal building controls in naturally ventilated buildings. [ABSTRACT FROM AUTHOR]

Background: Developmental dysplasia of the hip (DDH) is a prevalent orthopaedic disorder in children, and screening methods vary across regions due to local health policies. The purpose of this review is to systematise the different ultrasound screening strategies for detecting DDH in newborns in Europe. Methods: Eligible studies from the PubMed, Embase, and Scopus databases, published between 1 January 2018 and 18 March 2023, were included. The inclusion criteria specified a European origin, a focus on newborn human patients, and information on ultrasound for DDH detection. Results: In total, 45 studies were included, covering 18 countries. Among them, six nations (Austria, Bosnia and Herzegovina, Poland, Slovenia, the Czech Republic, and Germany) perform universal ultrasound screening. The timing of the first ultrasound varies, with Austria and the Czech Republic within the 1st week, Bosnia and Herzegovina on the day of birth, Poland between 1 and 12 weeks, and Germany before the 6th week. The Graf method is the most popular ultrasound technique used. Conclusions: There is no consensus on the optimal DDH detection approach in Europe. Varied screening methods stem from epidemiological, cultural, and economic differences among countries. [ABSTRACT FROM AUTHOR]

To reduce the number of COVID-19 cases, vaccines were rapidly made available worldwide. For a strategically targeted response to the COVID-19 pandemic, population vaccination coverage was to be maximized. The target groups also included healthy children. In this context, it is important to understand the determinants and beliefs that lead parents to favor or oppose COVID-19 immunization in children. This study aimed to investigate parents' COVID-19 vaccination willingness in Germany for children aged 5–11 years in 2021/2022. For this purpose, the determinants and beliefs behind parents' vaccination decisions were examined. Descriptive analysis and bivariate correlations were performed on COVID-19 vaccination willingness and parents' mental health status, general vaccination attitudes, and SARS-CoV-2 politics perceptions. In total, 2401 participants fully participated in this cross-sectional study. The COVID-19 vaccination uptake (71.4%) outweighed the vaccination refusal (19.4%). Correlations revealed higher vaccine acceptance in parents presenting full vaccination certificates (90.9%), COVID-19 immunizations (99.9%), or increased COVID-19 fear (93.6%). Vaccination-refusal was associated with higher perceived pressure by COVID-19 vaccination campaigns (87.7%), higher experienced restrictions due to COVID-19 protective measures in parents' social environment (83.6%), and engagement against COVID-19 protective measures (51.6%). Besides general anxiety, no significant correlations were observed between parents' mental health variables and vaccination willingness. Although several factors are ultimately associated with vaccination willingness, future vaccination campaigns should prioritize reducing pressure, increasing trust, and considering parents' differentiation between familiar and unfamiliar pathogens during their vaccination decision-making process. [ABSTRACT FROM AUTHOR]

Regional fertility forecasts are important for long-term planning in a variety of fields that include future birth numbers in their forecast, such as school or kindergarten planning. They are one of the major components of regional population forecasts as well. Therefore, it is important to construct reliable forecasts that are based on sophisticated models that cover the high complexity of future regional fertility. We suggest a novel forecast model for forecasting regional age-specific fertility rates that covers long-term trends by time series models, demographic and regional correlations by principal component analysis, and future uncertainty by Monte Carlo simulation. The model is applied to all German NUTS-3 regions (districts/Kreise) simultaneously, where we forecast all regional age-specific fertility rates through the period of 2022–2045. The results from the simulations are presented via median predictions with 75% prediction intervals of the regional total fertility rates. The simulation shows strong regional heterogeneities in long-term fertility trends that are associated with the historical background of Germany, housing supply for families, opportunities for education, and the strength of labor markets, inter alia. [ABSTRACT FROM AUTHOR]

While driving, stress is caused by situations in which the driver estimates their ability to manage the driving demands as insufficient or loses the capability to handle the situation. This leads to increased numbers of driver mistakes and traffic violations. Additional stressing factors are time pressure, road conditions, or dislike for driving. Therefore, stress affects driver and road safety. Stress is classified into two categories depending on its duration and the effects on the body and psyche: short-term eustress and constantly present distress, which causes degenerative effects. In this work, we focus on distress. Wearable sensors are handy tools for collecting biosignals like heart rate, activity, etc. Easy installation and non-intrusive nature make them convenient for calculating stress. This study focuses on the investigation of stress and its implications. Specifically, the research conducts an analysis of stress within a select group of individuals from both Spain and Germany. The primary objective is to examine the influence of recognized psychological factors, including personality traits such as neuroticism, extroversion, psychoticism, stress and road safety. The estimation of stress levels was accomplished through the collection of physiological parameters (R-R intervals) using a Polar H10 chest strap. We observed that personality traits, such as extroversion, exhibited similar trends during relaxation, with an average heart rate 6% higher in Spain and 3% higher in Germany. However, while driving, introverts, on average, experienced more stress, with rates 4% and 1% lower than extroverts in Spain and Germany, respectively. [ABSTRACT FROM AUTHOR]